Computational Communication Research

<p>CCR is an online only journal that encourages and facilitates the sharing of 1) developments in computational tools and methods, and 2) the application of computational methods to answer theoretical questions about (human) communication. (CCR is published by Amsterdam University Press (AUP))</p>

Call for Proposals (English edition) | Programming Historian

Computational Methods in Landscape Ecology - Current Landscape Ecology Reports

Purpose of Review Landscapes can be defined as mosaics of different land covers, habitats, ecosystems, or land-use systems. The link between spatial heterogeneous patterns and ecological processes is the core concept in the research field of landscape ecology. Nowadays, advanced computational methods are essential to the field due to its cross-disciplinary nature, the increasing availability of data, and the complexity of landscape systems. Recent Findings This review provides an overview of recent developments in computational methods that have advanced the research field of landscape ecology. We focus on key topics such as spatial patterns, connectivity, landscape genetics, sampling, simulations and modeling, and spatial planning. Summary The review highlights key innovations, challenges, and potential future directions in the field, emphasizing the role of computational methods in addressing complex ecological questions.

The success rate of processed predicted models in molecular replacement: implications for experimental phasing in the AlphaFold era

A large set of SAD-phased PDB depositions were tested for solubility by molecular replacement using AlphaFold2 and other approaches. The 3% of cases that were not solved help to show where experimental phasing efforts could be focused in the future.

Mila Oiva: Chasing Leninism with AI. Using Computational Methods to Trace Cultural Phenomena through Historical Audiovisual Materials

How can we trace intangible historical phenomena, such as worldviews, cultural representations, or cultural-political movements through large-scale audiovisual archives? While the hermeneutic tradition of close reading has long provided a foundation for analyzing small-scale historical materials, the rise of digital sources presents new challenges and opportunities. When engaging with vast datasets, the intuitive processes of … „Mila Oiva: Chasing Leninism with AI. Using Computational Methods to Trace Cultural Phenomena through Historical Audiovisual Materials“ weiterlesen

Exploratory Dialogue with AI: Essay Based on AI Drift Methodology — DAHJ

AI has the potential to transform the art world and the way artists work and produce. However, working with and understanding AI, as a creation tool, raises a series of questions in relation to its internal functioning, its ethical implications, and how human critical capacity intervenes in the man-

Ausschreibungen : Akademie der Wissenschaften und der Literatur | Mainz

Does Data Science Enrich Art History? — Harald Klinke

The Artl@s Lectures for the 2023-2024 academic year focus on "Narrowing the Divide: A Dialogue between Art History and Digital Art History." Digital Art History is emerging as a distinct discipline but faces challenges in generating meaningful insights due to a gap between computational me